TRandom

Class Description


 TRandom

 basic Random number generator class (periodicity = 10**9).
 Note that this is a very simple generator (linear congruential)
 which is known to have defects (the lower random bits are correlated)
 and therefore should NOT be used in any statistical study.
 One should use instead TRandom1, TRandom2 or TRandom3.
 TRandom3, is based on the "Mersenne Twister generator", and is the recommended one,
 since it has good random proprieties (period of about 10**6000 ) and it is fast.
 TRandom1, based on the RANLUX algorithm, has mathematically proven random proprieties
 and a period of about 10**171. It is however slower than the others.
 TRandom2, is based on the Tausworthe generator of L'Ecuyer, and it has the advantage
 of being fast and using only 3 words (of 32 bits) for the state. The period is 10**26.

 The following table shows some timings (in nanoseconds/call)
 for the random numbers obtained using an Intel Pentium 3.0 GHz running Linux
 and using the gcc 3.2.3 compiler

    TRandom           34   ns/call     (BAD Generator)
    TRandom1          242  ns/call
    TRandom2          37   ns/call
    TRandom3          45   ns/call


 The following basic Random distributions are provided:
 ===================================================
   -Exp(tau)
   -Integer(imax)
   -Gaus(mean,sigma)
   -Rndm()
   -Uniform(x1)
   -Landau(mpv,sigma)
   -Poisson(mean)
   -Binomial(ntot,prob)

 Random numbers distributed according to 1-d, 2-d or 3-d distributions
 =====================================================================
 contained in TF1, TF2 or TF3 objects.
 For example, to get a random number distributed following abs(sin(x)/x)*sqrt(x)
 you can do:
   TF1 *f1 = new TF1("f1","abs(sin(x)/x)*sqrt(x)",0,10);
   double r = f1->GetRandom();
 The technique of using a TF1,2 or 3 function is very powerful.
 It is also more precise than using the basic functions (except Rndm).
 With a TF1 function, for example, the real integral of the function
 is correctly calculated in the specified range of the function.
 Getting a number from a TF1 function is also very fast.
 The following table shows some timings (in microsecons/call)
 for basic functions and TF1 functions.
 The left column is with the compiler, the right column with CINT.
 Numbers have been obtained on a Pentium 233Mhz running Linux.

                          g++        CINT
   Rndm..............    0.330       4.15
   Gaus..............    2.220       6.77
   Landau............   21.590      46.82
   Binomial(5,0.5)...    0.890       5.34
   Binomial(15,0.5)..    0.920       5.36
   Poisson(3)........    2.170       5.93
   Poisson(10).......    4.160       7.95
   Poisson(70).......   21.510      25.27
   Poisson(100)......    2.910       6.72
   GausTF1...........    2.070       4.73
   LandauTF1.........    2.100       4.73

  Note that the time to generate a number from an arbitrary TF1 function
  is independent of the complexity of the function.
  For Landau distribution, it is recommended to use the TF1 technique.

  TH1::FillRandom(TH1 *) or TH1::FillRandom(const char *tf1name)
  ==============================================================
  can be used to fill an histogram (1-d, 2-d, 3-d from an existing histogram
  or from an existing function.

  Note this interesting feature when working with objects
  =======================================================
  You can use several TRandom objects, each with their "independent"
  random sequence. For example, one can imagine
     TRandom *eventGenerator = new TRandom();
     TRandom *tracking       = new TRandom();
  eventGenerator can be used to generate the event kinematics.
  tracking can be used to track the generated particles with random numbers
  independent from eventGenerator.
  This very interesting feature gives the possibility to work with simple
  and very fast random number generators without worrying about
  random number periodicity as it was the case with Fortran.
  One can use TRandom::SetSeed to modify the seed of one generator.

  a TRandom object may be written to a Root file
  ==============================================
    -as part of another object
    -or with its own key (example gRandom->Write("Random");

  The small program below has been used to get the values in the table above.
   #ifndef __CINT__
      #include "TROOT.h"
   #include "TF1.h"
   #include "TRandom.h"
   #include "TStopwatch.h"
   void rand();

   //______________________________________________________________________________
   int main()
   {
     TROOT simple("simple","Test of random numbers");

     rand();
   }
   #endif
   void rand() {
     int i, N = 1000000;
     double cpn = 1000000./N;
     double x;
     TStopwatch sw;
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Rndm(i);
     }
     printf("Rndm.............. %8.3f microseconds/call\n",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Gaus(0,1);
     }
     printf("Gaus.............. %8.3f\n",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Landau(0,1);
     }
     printf("Landau............ %8.3f\n",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Binomial(5,0.5);
     }
     printf("Binomial(5,0.5)... %8.3f\n",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Binomial(15,0.5);
     }
     printf("Binomial(15,0.5).. %8.3f\n",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Poisson(3);
     }
     printf("Poisson(3)........ %8.3f\n",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Poisson(10);
     }
     printf("Poisson(10)....... %8.3f\n",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Poisson(70);
     }
     printf("Poisson(70)....... %8.3f\n",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Poisson(100);
     }
     printf("Poisson(100)...... %8.3f\n",sw.CpuTime()*cpn);

     TF1 *f1 = new TF1("f1","gaus",-4,4);
     f1->SetParameters(1,0,1);
     sw.Start();
     for (i=0;i<N;i++) {
        x = f1->GetRandom();
     }
     printf("GausTF1........... %8.3f\n",sw.CpuTime()*cpn);

     TF1 *f2 = new TF1("f2","landau",-5,15);
     f2->SetParameters(1,0,1);
     sw.Start();
     for (i=0;i<N;i++) {
        x = f2->GetRandom();
     }
     printf("LandauTF1......... %8.3f\n",sw.CpuTime()*cpn);

   }
TRandom

class TRandom : public TNamed

Data Members

Class Description
